Ordering in ternary nitride semiconducting alloys

We present a thorough theoretical study of ordering phenomena in nitride ternary alloys GaInN, AlInN, and AlGaN. Using the Monte Carlo approach and energetics based on the Keating model we analyze the influence of various factors on ordering in bulk crystals and epitaxial layers. We characterize the degree of both short range order (SRO) and long ranger order (LRO) for different compositions, temperatures and for substrates associated with different epitaxial strain. For the description of the SRO the Warren-Cowley parameters related to the first four coordination shells are used. The LRO is detected by means of the introduced sim-LRO parameter, based on the Bragg-Williams approach. The description of the observed long-range ordering patterns and conditions for their occurrence follows

A comparative DFT study of electronic properties of 2H-, 4H- and 6H-SiC(0001) and SiC(000-1) clean surfaces: Significance of the surface Stark effect

Electric field, uniform within the slab, emerging due to Fermi level pinning at its both sides is analyzed using DFT simulations of the SiC surface slabs of different thickness. It is shown that for thicker slab the field is nonuniform and this fact is related to the surface state charge. Using the electron density and potential profiles it is proved that for high precision simulations it is necessary to take into account enough number of the Si-C layers. We show that using 12 diatomic layers leads to satisfactory results. It is also demonstrated that the change of the opposite side slab termination, both by different type of atoms or by their location, can be used to adjust electric field within the slab, creating a tool for simulation of surface properties, depending on the doping in the bulk of semiconductor. Using these simulations it was found that, depending on the electric field, the energy of the surface states changes in a different way than energy of the bulk states. This criterion can be used to distinguish Shockley and Tamm surface states. The electronic properties, i.e. energy and type of surface states of the three clean surfaces: 2H-, 4H-, 6H-SiC(0001), and SiC($000 \bar{1}$) are analyzed and compared using field dependent DFT simulations.Comment: 18 pages, 10 figures, 4 table

A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection

The response to respiratory viruses varies substantially between individuals, and there are currently no known molecular predictors from the early stages of infection. Here we conduct a community-based analysis to determine whether pre- or early post-exposure molecular factors could predict physiologic responses to viral exposure. Using peripheral blood gene expression profiles collected from healthy subjects prior to exposure to one of four respiratory viruses (H1N1, H3N2, Rhinovirus, and RSV), as well as up to 24 h following exposure, we find that it is possible to construct models predictive of symptomatic response using profiles even prior to viral exposure. Analysis of predictive gene features reveal little overlap among models; however, in aggregate, these genes are enriched for common pathways. Heme metabolism, the most significantly enriched pathway, is associated with a higher risk of developing symptoms following viral exposure. This study demonstrates that pre-exposure molecular predictors can be identified and improves our understanding of the mechanisms of response to respiratory viruses